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AI-driven drug discovery aims to close the data loop amid rising costs

Drug discovery costs have doubled every nine years since the 1950s, with new drugs taking 10-15 years to develop. AI is being leveraged to address these challenges by closing the data loop in the drug development process.

Source: MIT Technology Review AI · technologyreview.com Published 2026-07-27T11:40:16+00:00 Detected 2026-07-27T13:22:26+00:00
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Drug discovery costs have doubled every nine years since the 1950s, with new drugs taking 10-15 years to develop. AI is being leveraged to address these challenges by closing the data loop in the drug development process.

AI-assisted summary based on the listed source.

Drug discovery is a high-cost, high-risk endeavor that is under growing pressure from a market increasingly defined by first-mover advantage. Since the 1950s, the cost of developing new pharmaceuticals has roughly doubled every nine years—a phenomenon known as Eroom’s Law. Today, bringing a new drug to market...

Reducing time and cost in drug discovery could accelerate bringing new pharmaceuticals to market, offering a competitive edge in a high-risk industry. AI's role in managing and utilizing data more effectively may help overcome longstanding inefficiencies.

Signal Strength 88% Technical label SOURCE-BACKED Public Interest 26 Category USEFUL NOW Reader Depth PRACTICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 0 Novelty Interest Score 94 Consequence Score 18 Curiosity Score 0 Shareability Score 45

VQV surfaced this signal because it is recent, relevant to AI Search, connected to MIT Technology Review AI.